SlideShare a Scribd company logo
Cognos Data Module
Architectures & Use Cases
1
Thumbnail
2
Hundreds of resources
Visit the Resource Library
on the Senturus website
to download this presentation
and explore other assets:
senturus.com/resources
2
3
Pedro Ining
Principle BI Analytics Architect
Senturus, Inc.
Michael Weinhauer
Director
Senturus, Inc.
3
Introductions
Agenda
• Introduction
• Cognos data module architectures
• Data set libraries
• Use cases
• Senturus overview
• Additional resources
4
Enjoy the full webinar presentation
This slide deck is from the webinar Cognos Data Module
Architectures & Use Cases.
To view the FREE video recording and download this deck,
go to https://senturus.com/resources/cognos-data-module-
architectures-and-use-cases/
5
Cognos data modules
• Web-based end-user focused data blending, modeling,
transformation tool debuted on Cognos Analytics 11.0
• IBM’s response to data democratization and other tools
like Tableau and Microsoft Power BI
• 11.1 R7 significantly closed some of the technical gaps
between Framework Manager and data modules
• All future development resources will be focused on
data module enhancements
6
What are data modules still missing?
• DMR (dimensionally modeled relational)
• Object-based security
• Model branches and merges – team-based modeling
• Parameter maps
• Multi-lingual packages
• Complex row-level security implementations
• FM style namespaces (but we can somewhat simulate)
• FM style packages
• Search and select prompt for reporting
7
Data governance is a framework for
ensuring the availability, accuracy,
and security of data across an
organization.
8
•IT driven enterprise model
•Hybrid model
•End-user driven model
Data module architectures
Many ways to use data modules, but we would like to
discuss potential key architectures that you can use to
implement data modules
9
IT driven enterprise model – classic FM
 IT gathers report
requirements
 IT develops the Framework
Manager model
 IT publishes packages from
the Framework Manager
model
 IT creates standard reports
from the package
 Users may create their own
ad hoc analysis reports from
the package
10
IT driven enterprise model – data modules
• Replace the use of FM with data modules
• For new modeling projects, they are driven by business requirements vs.
modeling the entire database
• For existing legacy FM models, select business relevant subject areas in the
model that need to be redesigned for better self-service
• The data module is READ ONLY and controlled by IT
• End user modelers can ‘link’ to this module or create data sets for their own
modeling purposes
11
Hybrid model
• Uses legacy IT
maintained FM
packages
• Part of the package
can be integrated
into a user or IT data
module
• Legacy packages
used to create
datasets for use in
data modules
• Allows user access
to spreadsheet data
12
End-user driven model
“Point me to the data, I’ll take care of the rest…”
 IT maintains the source
databases or data warehouses
 Use Cognos self-service
modeling components to model
the database for specific
requirements
 Users extract subsets of data
from source databases via
Cognos data sets technology;
which are integrated into data
modules
 Users may upload their own
privately maintained curated
data from spreadsheets or text
files
See demos of the three data module
architectures
To view the video recording and download the slide deck go
to https://senturus.com/resources/cognos-data-module-
architectures-and-use-cases/.
13
14
Data set libraries
• Common data sets for use in user or IT defined data modules
• Subject specific dimensional/reference data or summarized fact data
• Not meant to store large amounts of data, typically 10-15M rows max
• Allows for better performing queries/reports
• Stored in common folder structures
Databases FM Packages
Common Data Sets Stored in Team Content
Answers to participant questions
15
Cognos Data Module Architectures & Use
Cases
16
Q: Is it possible to connect multiple fact tables to the same dimension
table or multiple dimension tables in Cognos? For example, if we have five
fact tables and three DIM tables with four out of the five fact tables
connect to three DIM tables?
A: Yes, this typical star schema model is fully supported by data modules.
Q: If our users have read only access in Cognos, can they copy data
module from their “My Content” and make changes all join?
A: Much like a report, users can copy the data module to their My Content and
then make changes. But they are no longer linked to the READ ONLY data
module and will no longer see any more changes that IT may make.
Cognos Data Module Architectures & Use
Cases
17
Q: Users in our environment can see Frameworks, but within modules,
they can’t see tables in our data warehouse. Are there other
configuration/settings that we’re missing? For example, if users go to
Microsoft Access, can they see the tables within the warehouse?
A: When you create the Cognos data source connection be sure you load the
metadata for the schema. This is a button in the data source connection
properties.
Q: How many Cognos Framework Manager packages can be combined in
a data module?
A: There is no limit, but it really is a best practice design issue. Make sure your
data modules are concise and subject specific.
Cognos Data Module Architectures & Use
Cases
18
Q: How resource intensive are data modules compared to Framework
Manager? Does Cognos suggest additional resources if using DMs vs.
FM?
A: Since data modules can integrate many different types of data sources – DB
Connections, FM packages, data set and uploaded Excel files it will depend on
the content of the DMs. A DM with only data sets will generally perform better
but you may need to keep an eye on the memory use of the data sets in
Cognos.
Q: When combining a Cognos Framework Manager package with a data
module, does the FM package need to be built in DQM or can it be CQM?
A: The FM model needs to be in DQM.
Cognos Data Module Architectures & Use
Cases
19
Q: If I get an error when I try to bring an ODS package into the Cognos
data module will I need help from IT? It says connection information is
missing from data source (ODS). I do not have administrative access.
A: Like running a report against a package, if the data source connection of the
package contains incorrect connection settings, you will need access to that
connection. Try calling IT to fix the package connection.
Q: If the Cognos Framework Manager package can be either CQM or DQM,
are there any advantages or disadvantages between the two?
A: DQM is really the better of the two modes. It is the newest mode and uses a
64BIT java engine vs. the 32bit CQM engine. Most current and future Cognos
Analytics 11x features will require DQM connections.
Cognos Data Module Architectures & Use
Cases
20
Q: If I create a hybrid Cognos data module with query subjects that have
object-based security, will that security be preserved?
A: A data module that brings in Framework Manager package objects will
respect the security model of the FM package.
Q: In Cognos 11.1.7 can I copy query objects from reports to a data set?
A: The 11.1.7 release uses the query tools from the report studio tool set. But
we do not believe there is an easy was to import those query objects from
reports to the new 11.1.7 data set editor.
Q: How can I get the presentation for this webinar?
A: Access the deck and the recording at:
https://senturus.com/resources/cognos-data-module-architectures-use-cases/
Cognos Data Module Architectures & Use
Cases
21
Q: With the data set library, how do I save different Cognos data sets for
different departments since the data set is saved under the same name?
The security is based on department at my organization.
A: You can use Team Content folder security to create data sets for departments
in different folders. Then the folders are secured for each department. Beyond
data sets, you can have one master data set that is in a data module that
contains security based on Cognos security groups. Then the data module is
the one that is published and then users can link to that data module.
Q: Will the architecture model work in Cognos 11.0.13?
A: Possibly, but there are so many more data module features added through
the 11.1.7 release. We recommend not using that release.
Cognos Data Module Architectures & Use
Cases
22
Q: Would you recommend using data modules in Cognos 11.0.11?
A: We recommend waiting to upgrade to the latest release because of the many
improvements to data modules.
Q: How much RAM is used when using Cognos data sets?
A: Depends on the size of the data set. You can adjust how much memory
Cognos devotes to data sets in the advanced settings section of the admin
console. Initially it is set to 4GB.
Q: How are Cognos data modules validated?
A: They are automatically validated in the tool.
Cognos Data Module Architectures & Use
Cases
23
Q: To improve the performance of data modules, we’ve been creating data
sets with data modules and then bring it back to data module. Although this
process works, we have been facing issues when trying to combine
package. What are the shortcomings when using packages in data modules?
A: 11.1.7 has an improved data set editor. The full query painter tools in Report
Studio are available in the data set editor. You no longer need to create data
modules to create data sets. Using packages in data modules can become
confusing since you don’t really see the tables on the relationship diagram editor,
and this is by design because of the potential of seeing too many tables. We like to
only expose the tables we need from packages in DMs via views. We’ll analyze
the requirements and if possible, create a data set from that package that is more
subject focused and smaller than the full table in the package.
Cognos Data Module Architectures & Use
Cases
24
Q: How do Cognos datasets perform against cloud?
A: When you join a data set to a cloud table, Cognos will bring the data from the
cloud table and join it to the dataset at the Cognos server.
Q: Is there possible versioning on Cognos data modeling?
A: There is no native versioning so you will need to make copies of a data module.
However, Motio has versioning capabilities.
Q: In Cognos Framework Manager, can we do complex joins with SQL
statements? Can we do those complex joins in Cognos data modules as
well? Or are they limited to simple joins?
A: The later releases of data modules allow for complex joins. We recommend you
start your data module journey with the latest release of Cognos 11.1.7.
Cognos Data Module Architectures & Use
Cases
25
Q: Can we include several packages in Cognos data modules and then in
report editor join queries from various packages in the data modules?
A: Technically yes, but it will look messy to report writers. We advise exposing
what you need then hide the underlying packages in a data module.
Q: How can we make a translation layer in Cognos data modules for reusing
translations for role playing dimensions?
A: For role playing dimensions, bring in the physical dimension table. Make table
view copies of the table then hide the base physical table. Do this in a folder, it
acts like a physical namespace layer.
Cognos Data Module Architectures & Use
Cases
26
Q: When is the auto refresh capability arriving in Cognos? For example, we’d
like to use a flat file loaded from a drive. Every time the file is updated, we
need to reupload the file.
A: Great idea, but we’re not sure when that feature will be arriving. It might be
possible to do this via the SDK.
Q: Does IBM want users to move off Framework Manager and instead use
data modules?
A: For new modeling tasks IBM would like you to start with data modules. There
are so many Framework Manager models in use that we don’t advise doing a
complete 1 for 1 migration of an FM model to a DM. It’s better to just find what
parts of that model needs re-engineering and focus on those.
Cognos Data Module Architectures & Use
Cases
27
Q: Where is the data stored from data sets in Cognos?
A: They are stored on the Cognos server in a parquet file format.
Q: What are advantages and disadvantages to storing Cognos datasets in a
content store database vs. external files?
A: Initially they are stored in the content store, but we recommend storing it on the
file system because as your user base uses this feature, the content store is going
to get too large. With a file system you can devote specific storage locations that
could be optimized for retrieval.
Q: Does report execution mode changing to 64-bit help in Cognos datasets
and data modules or in general?
A: Yes.
The authority in
Business Intelligence
28
Exclusively focused on BI,
Senturus is unrivaled in its
expertise across the BI stack.
Decisions and actions
Business needs
Bridging the gap
29
Analysis-ready data
Full spectrum BI services
•Dashboards, reporting and visualizations
•Data preparation and modern data warehousing
•Hybrid BI environments (migrations, security, etc.)
•Software to enable bimodal BI and platform migrations
•BI support retainer (expertise on demand)
•Training and mentoring
30
A long, strong history of success
• 20+ years
• 1600+ clients
• 3000+ projects
31
Expand your
knowledge
32
Find more resources
on the Senturus website:
senturus.com/senturus-resources
Complete BI training
33
Instructor-led online courses Self-paced learning
Mentoring
Tailored group sessions
Additional resources
34
Insider viewpoints
Technical tips
Unbiased product reviews
Product demos Upcoming events
More on this subject
© 2020 by Senturus, Inc. This presentation may not be reused or distributed without the written consent of Senturus, Inc.
www.senturus.com 888 601 6010 info@senturus.com

More Related Content

What's hot

Big Data Analytics
Big Data AnalyticsBig Data Analytics
Big Data Analytics
humerashaziya
 
How to Take Advantage of an Enterprise Data Warehouse in the Cloud
How to Take Advantage of an Enterprise Data Warehouse in the CloudHow to Take Advantage of an Enterprise Data Warehouse in the Cloud
How to Take Advantage of an Enterprise Data Warehouse in the Cloud
Denodo
 
Enterprise Data Governance Framework With Change Management
Enterprise Data Governance Framework With Change ManagementEnterprise Data Governance Framework With Change Management
Enterprise Data Governance Framework With Change Management
SlideTeam
 
Slides: Data Monetization — Demonstrating Quantifiable Financial Benefits fro...
Slides: Data Monetization — Demonstrating Quantifiable Financial Benefits fro...Slides: Data Monetization — Demonstrating Quantifiable Financial Benefits fro...
Slides: Data Monetization — Demonstrating Quantifiable Financial Benefits fro...
DATAVERSITY
 
Data warehouse
Data warehouseData warehouse
Data warehouse
Rishabh Dogra
 
Data Warehousing using Hadoop
Data Warehousing using HadoopData Warehousing using Hadoop
Data Warehousing using Hadoop
DataWorks Summit
 
Data Governance Takes a Village (So Why is Everyone Hiding?)
Data Governance Takes a Village (So Why is Everyone Hiding?)Data Governance Takes a Village (So Why is Everyone Hiding?)
Data Governance Takes a Village (So Why is Everyone Hiding?)
DATAVERSITY
 
Snowflake: The Good, the Bad, and the Ugly
Snowflake: The Good, the Bad, and the UglySnowflake: The Good, the Bad, and the Ugly
Snowflake: The Good, the Bad, and the Ugly
Tyler Wishnoff
 
Azure Synapse Analytics Overview (r2)
Azure Synapse Analytics Overview (r2)Azure Synapse Analytics Overview (r2)
Azure Synapse Analytics Overview (r2)
James Serra
 
Snowflake Overview
Snowflake OverviewSnowflake Overview
Snowflake Overview
Snowflake Computing
 
Snowflake + Power BI: Cloud Analytics for Everyone
Snowflake + Power BI: Cloud Analytics for EveryoneSnowflake + Power BI: Cloud Analytics for Everyone
Snowflake + Power BI: Cloud Analytics for Everyone
Angel Abundez
 
Power BI: From the Basics
Power BI: From the BasicsPower BI: From the Basics
Power BI: From the Basics
Nikkia Carter
 
Intuit's Data Mesh - Data Mesh Leaning Community meetup 5.13.2021
Intuit's Data Mesh - Data Mesh Leaning Community meetup 5.13.2021Intuit's Data Mesh - Data Mesh Leaning Community meetup 5.13.2021
Intuit's Data Mesh - Data Mesh Leaning Community meetup 5.13.2021
Tristan Baker
 
Five Things to Consider About Data Mesh and Data Governance
Five Things to Consider About Data Mesh and Data GovernanceFive Things to Consider About Data Mesh and Data Governance
Five Things to Consider About Data Mesh and Data Governance
DATAVERSITY
 
Overview on Azure Machine Learning
Overview on Azure Machine LearningOverview on Azure Machine Learning
Overview on Azure Machine Learning
James Serra
 
Data, Information And Knowledge Management Framework And The Data Management ...
Data, Information And Knowledge Management Framework And The Data Management ...Data, Information And Knowledge Management Framework And The Data Management ...
Data, Information And Knowledge Management Framework And The Data Management ...
Alan McSweeney
 
Modern Business Intelligence - Design and Implementations
Modern Business Intelligence - Design and ImplementationsModern Business Intelligence - Design and Implementations
Modern Business Intelligence - Design and Implementations
David J Rosenthal
 
Building a Big Data Pipeline
Building a Big Data PipelineBuilding a Big Data Pipeline
Building a Big Data Pipeline
Jesus Rodriguez
 
Chapter 2 - Retail Sales
Chapter 2 - Retail Sales Chapter 2 - Retail Sales
Chapter 2 - Retail Sales
Khairul Shafee Kalid
 
Creating an Effective MDM Strategy for Salesforce
Creating an Effective MDM Strategy for SalesforceCreating an Effective MDM Strategy for Salesforce
Creating an Effective MDM Strategy for Salesforce
Perficient, Inc.
 

What's hot (20)

Big Data Analytics
Big Data AnalyticsBig Data Analytics
Big Data Analytics
 
How to Take Advantage of an Enterprise Data Warehouse in the Cloud
How to Take Advantage of an Enterprise Data Warehouse in the CloudHow to Take Advantage of an Enterprise Data Warehouse in the Cloud
How to Take Advantage of an Enterprise Data Warehouse in the Cloud
 
Enterprise Data Governance Framework With Change Management
Enterprise Data Governance Framework With Change ManagementEnterprise Data Governance Framework With Change Management
Enterprise Data Governance Framework With Change Management
 
Slides: Data Monetization — Demonstrating Quantifiable Financial Benefits fro...
Slides: Data Monetization — Demonstrating Quantifiable Financial Benefits fro...Slides: Data Monetization — Demonstrating Quantifiable Financial Benefits fro...
Slides: Data Monetization — Demonstrating Quantifiable Financial Benefits fro...
 
Data warehouse
Data warehouseData warehouse
Data warehouse
 
Data Warehousing using Hadoop
Data Warehousing using HadoopData Warehousing using Hadoop
Data Warehousing using Hadoop
 
Data Governance Takes a Village (So Why is Everyone Hiding?)
Data Governance Takes a Village (So Why is Everyone Hiding?)Data Governance Takes a Village (So Why is Everyone Hiding?)
Data Governance Takes a Village (So Why is Everyone Hiding?)
 
Snowflake: The Good, the Bad, and the Ugly
Snowflake: The Good, the Bad, and the UglySnowflake: The Good, the Bad, and the Ugly
Snowflake: The Good, the Bad, and the Ugly
 
Azure Synapse Analytics Overview (r2)
Azure Synapse Analytics Overview (r2)Azure Synapse Analytics Overview (r2)
Azure Synapse Analytics Overview (r2)
 
Snowflake Overview
Snowflake OverviewSnowflake Overview
Snowflake Overview
 
Snowflake + Power BI: Cloud Analytics for Everyone
Snowflake + Power BI: Cloud Analytics for EveryoneSnowflake + Power BI: Cloud Analytics for Everyone
Snowflake + Power BI: Cloud Analytics for Everyone
 
Power BI: From the Basics
Power BI: From the BasicsPower BI: From the Basics
Power BI: From the Basics
 
Intuit's Data Mesh - Data Mesh Leaning Community meetup 5.13.2021
Intuit's Data Mesh - Data Mesh Leaning Community meetup 5.13.2021Intuit's Data Mesh - Data Mesh Leaning Community meetup 5.13.2021
Intuit's Data Mesh - Data Mesh Leaning Community meetup 5.13.2021
 
Five Things to Consider About Data Mesh and Data Governance
Five Things to Consider About Data Mesh and Data GovernanceFive Things to Consider About Data Mesh and Data Governance
Five Things to Consider About Data Mesh and Data Governance
 
Overview on Azure Machine Learning
Overview on Azure Machine LearningOverview on Azure Machine Learning
Overview on Azure Machine Learning
 
Data, Information And Knowledge Management Framework And The Data Management ...
Data, Information And Knowledge Management Framework And The Data Management ...Data, Information And Knowledge Management Framework And The Data Management ...
Data, Information And Knowledge Management Framework And The Data Management ...
 
Modern Business Intelligence - Design and Implementations
Modern Business Intelligence - Design and ImplementationsModern Business Intelligence - Design and Implementations
Modern Business Intelligence - Design and Implementations
 
Building a Big Data Pipeline
Building a Big Data PipelineBuilding a Big Data Pipeline
Building a Big Data Pipeline
 
Chapter 2 - Retail Sales
Chapter 2 - Retail Sales Chapter 2 - Retail Sales
Chapter 2 - Retail Sales
 
Creating an Effective MDM Strategy for Salesforce
Creating an Effective MDM Strategy for SalesforceCreating an Effective MDM Strategy for Salesforce
Creating an Effective MDM Strategy for Salesforce
 

Similar to Cognos Data Module Architectures & Use Cases

Can Cognos Data Modules Replace Framework Manager?
Can Cognos Data Modules Replace Framework Manager?Can Cognos Data Modules Replace Framework Manager?
Can Cognos Data Modules Replace Framework Manager?
Senturus
 
Data Modeling Comparison: Tableau, Cognos and Power BI
Data Modeling Comparison: Tableau, Cognos and Power BIData Modeling Comparison: Tableau, Cognos and Power BI
Data Modeling Comparison: Tableau, Cognos and Power BI
Senturus
 
IBM Cognos Report Studio Version 10 Tips and Tricks – Webinar Q & A
IBM Cognos Report Studio Version 10 Tips and Tricks – Webinar Q & AIBM Cognos Report Studio Version 10 Tips and Tricks – Webinar Q & A
IBM Cognos Report Studio Version 10 Tips and Tricks – Webinar Q & A
Senturus
 
A Comparison of Power BI, Tableau & Cognos
A Comparison of Power BI, Tableau & CognosA Comparison of Power BI, Tableau & Cognos
A Comparison of Power BI, Tableau & Cognos
Senturus
 
Operationalizing the Value of MongoDB: The MetLife Experience
Operationalizing the Value of MongoDB: The MetLife ExperienceOperationalizing the Value of MongoDB: The MetLife Experience
Operationalizing the Value of MongoDB: The MetLife Experience
MongoDB
 
Questions Log: What’s New in Cognos BI Version 10.2.2
Questions Log: What’s New in Cognos BI Version 10.2.2Questions Log: What’s New in Cognos BI Version 10.2.2
Questions Log: What’s New in Cognos BI Version 10.2.2
Senturus
 
1989 Joyce: An Object-Oriented Decision Tree Builder
1989 Joyce: An Object-Oriented Decision Tree Builder1989 Joyce: An Object-Oriented Decision Tree Builder
1989 Joyce: An Object-Oriented Decision Tree Builder
Bob Marcus
 
Joyce: An Object-oriented Decision Tree Builder 1989
Joyce: An Object-oriented Decision Tree Builder 1989Joyce: An Object-oriented Decision Tree Builder 1989
Joyce: An Object-oriented Decision Tree Builder 1989
Bob Marcus
 
Fulltext01
Fulltext01Fulltext01
Fulltext01
navjeet11
 
Cognos Analytics November 2017 Enhancements: 11.0.8 Demos and Q&A with the IB...
Cognos Analytics November 2017 Enhancements: 11.0.8 Demos and Q&A with the IB...Cognos Analytics November 2017 Enhancements: 11.0.8 Demos and Q&A with the IB...
Cognos Analytics November 2017 Enhancements: 11.0.8 Demos and Q&A with the IB...
Senturus
 
Software Design PatternsConsider a company migrating to a third-p.pdf
Software Design PatternsConsider a company migrating to a third-p.pdfSoftware Design PatternsConsider a company migrating to a third-p.pdf
Software Design PatternsConsider a company migrating to a third-p.pdf
arorastores
 
Cognos Analytics Dashboards or Reports?
Cognos Analytics Dashboards or Reports?Cognos Analytics Dashboards or Reports?
Cognos Analytics Dashboards or Reports?
Senturus
 
IBM Cognos 10 Framework Manager in Action: Questions & Answers
IBM Cognos 10 Framework Manager in Action:  Questions & AnswersIBM Cognos 10 Framework Manager in Action:  Questions & Answers
IBM Cognos 10 Framework Manager in Action: Questions & Answers
Senturus
 
New Capabilities with Cognos Data Modules
New Capabilities with Cognos Data ModulesNew Capabilities with Cognos Data Modules
New Capabilities with Cognos Data Modules
Senturus
 
How to Create a Cognos Analytics Dashboard
How to Create a Cognos Analytics DashboardHow to Create a Cognos Analytics Dashboard
How to Create a Cognos Analytics Dashboard
Senturus
 
Q&A: Data Modules, Data Sets & Data Servers
Q&A: Data Modules, Data Sets & Data ServersQ&A: Data Modules, Data Sets & Data Servers
Q&A: Data Modules, Data Sets & Data Servers
Senturus
 
Bse 3105 lecture 4-software re-engineering
Bse 3105  lecture 4-software re-engineeringBse 3105  lecture 4-software re-engineering
Bse 3105 lecture 4-software re-engineering
Alonzee Tash
 
BigData Analysis
BigData AnalysisBigData Analysis
MS SQL Backups explained by a DBA
MS SQL Backups explained by a DBAMS SQL Backups explained by a DBA
MS SQL Backups explained by a DBA
Wally Pons
 
Ems
EmsEms

Similar to Cognos Data Module Architectures & Use Cases (20)

Can Cognos Data Modules Replace Framework Manager?
Can Cognos Data Modules Replace Framework Manager?Can Cognos Data Modules Replace Framework Manager?
Can Cognos Data Modules Replace Framework Manager?
 
Data Modeling Comparison: Tableau, Cognos and Power BI
Data Modeling Comparison: Tableau, Cognos and Power BIData Modeling Comparison: Tableau, Cognos and Power BI
Data Modeling Comparison: Tableau, Cognos and Power BI
 
IBM Cognos Report Studio Version 10 Tips and Tricks – Webinar Q & A
IBM Cognos Report Studio Version 10 Tips and Tricks – Webinar Q & AIBM Cognos Report Studio Version 10 Tips and Tricks – Webinar Q & A
IBM Cognos Report Studio Version 10 Tips and Tricks – Webinar Q & A
 
A Comparison of Power BI, Tableau & Cognos
A Comparison of Power BI, Tableau & CognosA Comparison of Power BI, Tableau & Cognos
A Comparison of Power BI, Tableau & Cognos
 
Operationalizing the Value of MongoDB: The MetLife Experience
Operationalizing the Value of MongoDB: The MetLife ExperienceOperationalizing the Value of MongoDB: The MetLife Experience
Operationalizing the Value of MongoDB: The MetLife Experience
 
Questions Log: What’s New in Cognos BI Version 10.2.2
Questions Log: What’s New in Cognos BI Version 10.2.2Questions Log: What’s New in Cognos BI Version 10.2.2
Questions Log: What’s New in Cognos BI Version 10.2.2
 
1989 Joyce: An Object-Oriented Decision Tree Builder
1989 Joyce: An Object-Oriented Decision Tree Builder1989 Joyce: An Object-Oriented Decision Tree Builder
1989 Joyce: An Object-Oriented Decision Tree Builder
 
Joyce: An Object-oriented Decision Tree Builder 1989
Joyce: An Object-oriented Decision Tree Builder 1989Joyce: An Object-oriented Decision Tree Builder 1989
Joyce: An Object-oriented Decision Tree Builder 1989
 
Fulltext01
Fulltext01Fulltext01
Fulltext01
 
Cognos Analytics November 2017 Enhancements: 11.0.8 Demos and Q&A with the IB...
Cognos Analytics November 2017 Enhancements: 11.0.8 Demos and Q&A with the IB...Cognos Analytics November 2017 Enhancements: 11.0.8 Demos and Q&A with the IB...
Cognos Analytics November 2017 Enhancements: 11.0.8 Demos and Q&A with the IB...
 
Software Design PatternsConsider a company migrating to a third-p.pdf
Software Design PatternsConsider a company migrating to a third-p.pdfSoftware Design PatternsConsider a company migrating to a third-p.pdf
Software Design PatternsConsider a company migrating to a third-p.pdf
 
Cognos Analytics Dashboards or Reports?
Cognos Analytics Dashboards or Reports?Cognos Analytics Dashboards or Reports?
Cognos Analytics Dashboards or Reports?
 
IBM Cognos 10 Framework Manager in Action: Questions & Answers
IBM Cognos 10 Framework Manager in Action:  Questions & AnswersIBM Cognos 10 Framework Manager in Action:  Questions & Answers
IBM Cognos 10 Framework Manager in Action: Questions & Answers
 
New Capabilities with Cognos Data Modules
New Capabilities with Cognos Data ModulesNew Capabilities with Cognos Data Modules
New Capabilities with Cognos Data Modules
 
How to Create a Cognos Analytics Dashboard
How to Create a Cognos Analytics DashboardHow to Create a Cognos Analytics Dashboard
How to Create a Cognos Analytics Dashboard
 
Q&A: Data Modules, Data Sets & Data Servers
Q&A: Data Modules, Data Sets & Data ServersQ&A: Data Modules, Data Sets & Data Servers
Q&A: Data Modules, Data Sets & Data Servers
 
Bse 3105 lecture 4-software re-engineering
Bse 3105  lecture 4-software re-engineeringBse 3105  lecture 4-software re-engineering
Bse 3105 lecture 4-software re-engineering
 
BigData Analysis
BigData AnalysisBigData Analysis
BigData Analysis
 
MS SQL Backups explained by a DBA
MS SQL Backups explained by a DBAMS SQL Backups explained by a DBA
MS SQL Backups explained by a DBA
 
Ems
EmsEms
Ems
 

More from Senturus

Power BI Gateway: Understanding, Installing, Configuring
Power BI Gateway: Understanding, Installing, ConfiguringPower BI Gateway: Understanding, Installing, Configuring
Power BI Gateway: Understanding, Installing, Configuring
Senturus
 
Cognos Performance Tuning Tips & Tricks
Cognos Performance Tuning Tips & TricksCognos Performance Tuning Tips & Tricks
Cognos Performance Tuning Tips & Tricks
Senturus
 
Power Automate for Power BI: Getting Started
Power Automate for Power BI: Getting StartedPower Automate for Power BI: Getting Started
Power Automate for Power BI: Getting Started
Senturus
 
Collaborative BI: 3 Ways to Use Cognos with Power BI & Tableau
Collaborative BI:  3 Ways to Use Cognos with Power BI & TableauCollaborative BI:  3 Ways to Use Cognos with Power BI & Tableau
Collaborative BI: 3 Ways to Use Cognos with Power BI & Tableau
Senturus
 
Tips for Installing Cognos Analytics 11.2.1x
Tips for Installing Cognos Analytics 11.2.1xTips for Installing Cognos Analytics 11.2.1x
Tips for Installing Cognos Analytics 11.2.1x
Senturus
 
How to Prepare for a BI Migration
How to Prepare for a BI MigrationHow to Prepare for a BI Migration
How to Prepare for a BI Migration
Senturus
 
4 Common Analytics Reporting Errors to Avoid
4 Common Analytics Reporting Errors to Avoid4 Common Analytics Reporting Errors to Avoid
4 Common Analytics Reporting Errors to Avoid
Senturus
 
Extending Power BI Functionality with R
Extending Power BI Functionality with RExtending Power BI Functionality with R
Extending Power BI Functionality with R
Senturus
 
Take Control of Your Cloud
Take Control of Your CloudTake Control of Your Cloud
Take Control of Your Cloud
Senturus
 
Using Python with Power BI
Using Python with Power BIUsing Python with Power BI
Using Python with Power BI
Senturus
 
User-Friendly Power BI Report Nav
User-Friendly Power BI Report NavUser-Friendly Power BI Report Nav
User-Friendly Power BI Report Nav
Senturus
 
Streamline Cognos Migrations & Consolidations
Streamline Cognos Migrations & ConsolidationsStreamline Cognos Migrations & Consolidations
Streamline Cognos Migrations & Consolidations
Senturus
 
What’s New in Cognos 11.2.1
What’s New in Cognos 11.2.1What’s New in Cognos 11.2.1
What’s New in Cognos 11.2.1
Senturus
 
Planning for a Power BI Enterprise Deployment
Planning for a Power BI Enterprise DeploymentPlanning for a Power BI Enterprise Deployment
Planning for a Power BI Enterprise Deployment
Senturus
 
Power BI Report Builder & Paginated Reports
Power BI Report Builder & Paginated Reports Power BI Report Builder & Paginated Reports
Power BI Report Builder & Paginated Reports
Senturus
 
Tableau: 6 Ways to Publish & Share Dashboards
Tableau: 6 Ways to Publish & Share DashboardsTableau: 6 Ways to Publish & Share Dashboards
Tableau: 6 Ways to Publish & Share Dashboards
Senturus
 
Cognos Analytics 11.2 New Features
Cognos Analytics 11.2 New FeaturesCognos Analytics 11.2 New Features
Cognos Analytics 11.2 New Features
Senturus
 
Azure Synapse vs. Snowflake: The Data Warehouse Dating Game
Azure Synapse vs. Snowflake: The Data Warehouse Dating GameAzure Synapse vs. Snowflake: The Data Warehouse Dating Game
Azure Synapse vs. Snowflake: The Data Warehouse Dating Game
Senturus
 
Secrets of High Performing Report Development Teams
Secrets of High Performing Report Development TeamsSecrets of High Performing Report Development Teams
Secrets of High Performing Report Development Teams
Senturus
 
Power BI: Data Cleansing & Power Query Editor
Power BI: Data Cleansing & Power Query EditorPower BI: Data Cleansing & Power Query Editor
Power BI: Data Cleansing & Power Query Editor
Senturus
 

More from Senturus (20)

Power BI Gateway: Understanding, Installing, Configuring
Power BI Gateway: Understanding, Installing, ConfiguringPower BI Gateway: Understanding, Installing, Configuring
Power BI Gateway: Understanding, Installing, Configuring
 
Cognos Performance Tuning Tips & Tricks
Cognos Performance Tuning Tips & TricksCognos Performance Tuning Tips & Tricks
Cognos Performance Tuning Tips & Tricks
 
Power Automate for Power BI: Getting Started
Power Automate for Power BI: Getting StartedPower Automate for Power BI: Getting Started
Power Automate for Power BI: Getting Started
 
Collaborative BI: 3 Ways to Use Cognos with Power BI & Tableau
Collaborative BI:  3 Ways to Use Cognos with Power BI & TableauCollaborative BI:  3 Ways to Use Cognos with Power BI & Tableau
Collaborative BI: 3 Ways to Use Cognos with Power BI & Tableau
 
Tips for Installing Cognos Analytics 11.2.1x
Tips for Installing Cognos Analytics 11.2.1xTips for Installing Cognos Analytics 11.2.1x
Tips for Installing Cognos Analytics 11.2.1x
 
How to Prepare for a BI Migration
How to Prepare for a BI MigrationHow to Prepare for a BI Migration
How to Prepare for a BI Migration
 
4 Common Analytics Reporting Errors to Avoid
4 Common Analytics Reporting Errors to Avoid4 Common Analytics Reporting Errors to Avoid
4 Common Analytics Reporting Errors to Avoid
 
Extending Power BI Functionality with R
Extending Power BI Functionality with RExtending Power BI Functionality with R
Extending Power BI Functionality with R
 
Take Control of Your Cloud
Take Control of Your CloudTake Control of Your Cloud
Take Control of Your Cloud
 
Using Python with Power BI
Using Python with Power BIUsing Python with Power BI
Using Python with Power BI
 
User-Friendly Power BI Report Nav
User-Friendly Power BI Report NavUser-Friendly Power BI Report Nav
User-Friendly Power BI Report Nav
 
Streamline Cognos Migrations & Consolidations
Streamline Cognos Migrations & ConsolidationsStreamline Cognos Migrations & Consolidations
Streamline Cognos Migrations & Consolidations
 
What’s New in Cognos 11.2.1
What’s New in Cognos 11.2.1What’s New in Cognos 11.2.1
What’s New in Cognos 11.2.1
 
Planning for a Power BI Enterprise Deployment
Planning for a Power BI Enterprise DeploymentPlanning for a Power BI Enterprise Deployment
Planning for a Power BI Enterprise Deployment
 
Power BI Report Builder & Paginated Reports
Power BI Report Builder & Paginated Reports Power BI Report Builder & Paginated Reports
Power BI Report Builder & Paginated Reports
 
Tableau: 6 Ways to Publish & Share Dashboards
Tableau: 6 Ways to Publish & Share DashboardsTableau: 6 Ways to Publish & Share Dashboards
Tableau: 6 Ways to Publish & Share Dashboards
 
Cognos Analytics 11.2 New Features
Cognos Analytics 11.2 New FeaturesCognos Analytics 11.2 New Features
Cognos Analytics 11.2 New Features
 
Azure Synapse vs. Snowflake: The Data Warehouse Dating Game
Azure Synapse vs. Snowflake: The Data Warehouse Dating GameAzure Synapse vs. Snowflake: The Data Warehouse Dating Game
Azure Synapse vs. Snowflake: The Data Warehouse Dating Game
 
Secrets of High Performing Report Development Teams
Secrets of High Performing Report Development TeamsSecrets of High Performing Report Development Teams
Secrets of High Performing Report Development Teams
 
Power BI: Data Cleansing & Power Query Editor
Power BI: Data Cleansing & Power Query EditorPower BI: Data Cleansing & Power Query Editor
Power BI: Data Cleansing & Power Query Editor
 

Recently uploaded

Analysis insight about a Flyball dog competition team's performance
Analysis insight about a Flyball dog competition team's performanceAnalysis insight about a Flyball dog competition team's performance
Analysis insight about a Flyball dog competition team's performance
roli9797
 
Learn SQL from basic queries to Advance queries
Learn SQL from basic queries to Advance queriesLearn SQL from basic queries to Advance queries
Learn SQL from basic queries to Advance queries
manishkhaire30
 
06-12-2024-BudapestDataForum-BuildingReal-timePipelineswithFLaNK AIM
06-12-2024-BudapestDataForum-BuildingReal-timePipelineswithFLaNK AIM06-12-2024-BudapestDataForum-BuildingReal-timePipelineswithFLaNK AIM
06-12-2024-BudapestDataForum-BuildingReal-timePipelineswithFLaNK AIM
Timothy Spann
 
The Building Blocks of QuestDB, a Time Series Database
The Building Blocks of QuestDB, a Time Series DatabaseThe Building Blocks of QuestDB, a Time Series Database
The Building Blocks of QuestDB, a Time Series Database
javier ramirez
 
Palo Alto Cortex XDR presentation .......
Palo Alto Cortex XDR presentation .......Palo Alto Cortex XDR presentation .......
Palo Alto Cortex XDR presentation .......
Sachin Paul
 
办(uts毕业证书)悉尼科技大学毕业证学历证书原版一模一样
办(uts毕业证书)悉尼科技大学毕业证学历证书原版一模一样办(uts毕业证书)悉尼科技大学毕业证学历证书原版一模一样
办(uts毕业证书)悉尼科技大学毕业证学历证书原版一模一样
apvysm8
 
Udemy_2024_Global_Learning_Skills_Trends_Report (1).pdf
Udemy_2024_Global_Learning_Skills_Trends_Report (1).pdfUdemy_2024_Global_Learning_Skills_Trends_Report (1).pdf
Udemy_2024_Global_Learning_Skills_Trends_Report (1).pdf
Fernanda Palhano
 
Global Situational Awareness of A.I. and where its headed
Global Situational Awareness of A.I. and where its headedGlobal Situational Awareness of A.I. and where its headed
Global Situational Awareness of A.I. and where its headed
vikram sood
 
The Ipsos - AI - Monitor 2024 Report.pdf
The  Ipsos - AI - Monitor 2024 Report.pdfThe  Ipsos - AI - Monitor 2024 Report.pdf
The Ipsos - AI - Monitor 2024 Report.pdf
Social Samosa
 
ViewShift: Hassle-free Dynamic Policy Enforcement for Every Data Lake
ViewShift: Hassle-free Dynamic Policy Enforcement for Every Data LakeViewShift: Hassle-free Dynamic Policy Enforcement for Every Data Lake
ViewShift: Hassle-free Dynamic Policy Enforcement for Every Data Lake
Walaa Eldin Moustafa
 
End-to-end pipeline agility - Berlin Buzzwords 2024
End-to-end pipeline agility - Berlin Buzzwords 2024End-to-end pipeline agility - Berlin Buzzwords 2024
End-to-end pipeline agility - Berlin Buzzwords 2024
Lars Albertsson
 
原版一比一利兹贝克特大学毕业证(LeedsBeckett毕业证书)如何办理
原版一比一利兹贝克特大学毕业证(LeedsBeckett毕业证书)如何办理原版一比一利兹贝克特大学毕业证(LeedsBeckett毕业证书)如何办理
原版一比一利兹贝克特大学毕业证(LeedsBeckett毕业证书)如何办理
wyddcwye1
 
原版制作(unimelb毕业证书)墨尔本大学毕业证Offer一模一样
原版制作(unimelb毕业证书)墨尔本大学毕业证Offer一模一样原版制作(unimelb毕业证书)墨尔本大学毕业证Offer一模一样
原版制作(unimelb毕业证书)墨尔本大学毕业证Offer一模一样
ihavuls
 
Experts live - Improving user adoption with AI
Experts live - Improving user adoption with AIExperts live - Improving user adoption with AI
Experts live - Improving user adoption with AI
jitskeb
 
A presentation that explain the Power BI Licensing
A presentation that explain the Power BI LicensingA presentation that explain the Power BI Licensing
A presentation that explain the Power BI Licensing
AlessioFois2
 
DATA COMMS-NETWORKS YR2 lecture 08 NAT & CLOUD.docx
DATA COMMS-NETWORKS YR2 lecture 08 NAT & CLOUD.docxDATA COMMS-NETWORKS YR2 lecture 08 NAT & CLOUD.docx
DATA COMMS-NETWORKS YR2 lecture 08 NAT & CLOUD.docx
SaffaIbrahim1
 
一比一原版(GWU,GW文凭证书)乔治·华盛顿大学毕业证如何办理
一比一原版(GWU,GW文凭证书)乔治·华盛顿大学毕业证如何办理一比一原版(GWU,GW文凭证书)乔治·华盛顿大学毕业证如何办理
一比一原版(GWU,GW文凭证书)乔治·华盛顿大学毕业证如何办理
bopyb
 
Open Source Contributions to Postgres: The Basics POSETTE 2024
Open Source Contributions to Postgres: The Basics POSETTE 2024Open Source Contributions to Postgres: The Basics POSETTE 2024
Open Source Contributions to Postgres: The Basics POSETTE 2024
ElizabethGarrettChri
 
一比一原版(UMN文凭证书)明尼苏达大学毕业证如何办理
一比一原版(UMN文凭证书)明尼苏达大学毕业证如何办理一比一原版(UMN文凭证书)明尼苏达大学毕业证如何办理
一比一原版(UMN文凭证书)明尼苏达大学毕业证如何办理
nyfuhyz
 
一比一原版(UCSB文凭证书)圣芭芭拉分校毕业证如何办理
一比一原版(UCSB文凭证书)圣芭芭拉分校毕业证如何办理一比一原版(UCSB文凭证书)圣芭芭拉分校毕业证如何办理
一比一原版(UCSB文凭证书)圣芭芭拉分校毕业证如何办理
nuttdpt
 

Recently uploaded (20)

Analysis insight about a Flyball dog competition team's performance
Analysis insight about a Flyball dog competition team's performanceAnalysis insight about a Flyball dog competition team's performance
Analysis insight about a Flyball dog competition team's performance
 
Learn SQL from basic queries to Advance queries
Learn SQL from basic queries to Advance queriesLearn SQL from basic queries to Advance queries
Learn SQL from basic queries to Advance queries
 
06-12-2024-BudapestDataForum-BuildingReal-timePipelineswithFLaNK AIM
06-12-2024-BudapestDataForum-BuildingReal-timePipelineswithFLaNK AIM06-12-2024-BudapestDataForum-BuildingReal-timePipelineswithFLaNK AIM
06-12-2024-BudapestDataForum-BuildingReal-timePipelineswithFLaNK AIM
 
The Building Blocks of QuestDB, a Time Series Database
The Building Blocks of QuestDB, a Time Series DatabaseThe Building Blocks of QuestDB, a Time Series Database
The Building Blocks of QuestDB, a Time Series Database
 
Palo Alto Cortex XDR presentation .......
Palo Alto Cortex XDR presentation .......Palo Alto Cortex XDR presentation .......
Palo Alto Cortex XDR presentation .......
 
办(uts毕业证书)悉尼科技大学毕业证学历证书原版一模一样
办(uts毕业证书)悉尼科技大学毕业证学历证书原版一模一样办(uts毕业证书)悉尼科技大学毕业证学历证书原版一模一样
办(uts毕业证书)悉尼科技大学毕业证学历证书原版一模一样
 
Udemy_2024_Global_Learning_Skills_Trends_Report (1).pdf
Udemy_2024_Global_Learning_Skills_Trends_Report (1).pdfUdemy_2024_Global_Learning_Skills_Trends_Report (1).pdf
Udemy_2024_Global_Learning_Skills_Trends_Report (1).pdf
 
Global Situational Awareness of A.I. and where its headed
Global Situational Awareness of A.I. and where its headedGlobal Situational Awareness of A.I. and where its headed
Global Situational Awareness of A.I. and where its headed
 
The Ipsos - AI - Monitor 2024 Report.pdf
The  Ipsos - AI - Monitor 2024 Report.pdfThe  Ipsos - AI - Monitor 2024 Report.pdf
The Ipsos - AI - Monitor 2024 Report.pdf
 
ViewShift: Hassle-free Dynamic Policy Enforcement for Every Data Lake
ViewShift: Hassle-free Dynamic Policy Enforcement for Every Data LakeViewShift: Hassle-free Dynamic Policy Enforcement for Every Data Lake
ViewShift: Hassle-free Dynamic Policy Enforcement for Every Data Lake
 
End-to-end pipeline agility - Berlin Buzzwords 2024
End-to-end pipeline agility - Berlin Buzzwords 2024End-to-end pipeline agility - Berlin Buzzwords 2024
End-to-end pipeline agility - Berlin Buzzwords 2024
 
原版一比一利兹贝克特大学毕业证(LeedsBeckett毕业证书)如何办理
原版一比一利兹贝克特大学毕业证(LeedsBeckett毕业证书)如何办理原版一比一利兹贝克特大学毕业证(LeedsBeckett毕业证书)如何办理
原版一比一利兹贝克特大学毕业证(LeedsBeckett毕业证书)如何办理
 
原版制作(unimelb毕业证书)墨尔本大学毕业证Offer一模一样
原版制作(unimelb毕业证书)墨尔本大学毕业证Offer一模一样原版制作(unimelb毕业证书)墨尔本大学毕业证Offer一模一样
原版制作(unimelb毕业证书)墨尔本大学毕业证Offer一模一样
 
Experts live - Improving user adoption with AI
Experts live - Improving user adoption with AIExperts live - Improving user adoption with AI
Experts live - Improving user adoption with AI
 
A presentation that explain the Power BI Licensing
A presentation that explain the Power BI LicensingA presentation that explain the Power BI Licensing
A presentation that explain the Power BI Licensing
 
DATA COMMS-NETWORKS YR2 lecture 08 NAT & CLOUD.docx
DATA COMMS-NETWORKS YR2 lecture 08 NAT & CLOUD.docxDATA COMMS-NETWORKS YR2 lecture 08 NAT & CLOUD.docx
DATA COMMS-NETWORKS YR2 lecture 08 NAT & CLOUD.docx
 
一比一原版(GWU,GW文凭证书)乔治·华盛顿大学毕业证如何办理
一比一原版(GWU,GW文凭证书)乔治·华盛顿大学毕业证如何办理一比一原版(GWU,GW文凭证书)乔治·华盛顿大学毕业证如何办理
一比一原版(GWU,GW文凭证书)乔治·华盛顿大学毕业证如何办理
 
Open Source Contributions to Postgres: The Basics POSETTE 2024
Open Source Contributions to Postgres: The Basics POSETTE 2024Open Source Contributions to Postgres: The Basics POSETTE 2024
Open Source Contributions to Postgres: The Basics POSETTE 2024
 
一比一原版(UMN文凭证书)明尼苏达大学毕业证如何办理
一比一原版(UMN文凭证书)明尼苏达大学毕业证如何办理一比一原版(UMN文凭证书)明尼苏达大学毕业证如何办理
一比一原版(UMN文凭证书)明尼苏达大学毕业证如何办理
 
一比一原版(UCSB文凭证书)圣芭芭拉分校毕业证如何办理
一比一原版(UCSB文凭证书)圣芭芭拉分校毕业证如何办理一比一原版(UCSB文凭证书)圣芭芭拉分校毕业证如何办理
一比一原版(UCSB文凭证书)圣芭芭拉分校毕业证如何办理
 

Cognos Data Module Architectures & Use Cases

  • 1. Cognos Data Module Architectures & Use Cases 1 Thumbnail
  • 2. 2 Hundreds of resources Visit the Resource Library on the Senturus website to download this presentation and explore other assets: senturus.com/resources 2
  • 3. 3 Pedro Ining Principle BI Analytics Architect Senturus, Inc. Michael Weinhauer Director Senturus, Inc. 3 Introductions
  • 4. Agenda • Introduction • Cognos data module architectures • Data set libraries • Use cases • Senturus overview • Additional resources 4
  • 5. Enjoy the full webinar presentation This slide deck is from the webinar Cognos Data Module Architectures & Use Cases. To view the FREE video recording and download this deck, go to https://senturus.com/resources/cognos-data-module- architectures-and-use-cases/ 5
  • 6. Cognos data modules • Web-based end-user focused data blending, modeling, transformation tool debuted on Cognos Analytics 11.0 • IBM’s response to data democratization and other tools like Tableau and Microsoft Power BI • 11.1 R7 significantly closed some of the technical gaps between Framework Manager and data modules • All future development resources will be focused on data module enhancements 6
  • 7. What are data modules still missing? • DMR (dimensionally modeled relational) • Object-based security • Model branches and merges – team-based modeling • Parameter maps • Multi-lingual packages • Complex row-level security implementations • FM style namespaces (but we can somewhat simulate) • FM style packages • Search and select prompt for reporting 7
  • 8. Data governance is a framework for ensuring the availability, accuracy, and security of data across an organization. 8 •IT driven enterprise model •Hybrid model •End-user driven model Data module architectures Many ways to use data modules, but we would like to discuss potential key architectures that you can use to implement data modules
  • 9. 9 IT driven enterprise model – classic FM  IT gathers report requirements  IT develops the Framework Manager model  IT publishes packages from the Framework Manager model  IT creates standard reports from the package  Users may create their own ad hoc analysis reports from the package
  • 10. 10 IT driven enterprise model – data modules • Replace the use of FM with data modules • For new modeling projects, they are driven by business requirements vs. modeling the entire database • For existing legacy FM models, select business relevant subject areas in the model that need to be redesigned for better self-service • The data module is READ ONLY and controlled by IT • End user modelers can ‘link’ to this module or create data sets for their own modeling purposes
  • 11. 11 Hybrid model • Uses legacy IT maintained FM packages • Part of the package can be integrated into a user or IT data module • Legacy packages used to create datasets for use in data modules • Allows user access to spreadsheet data
  • 12. 12 End-user driven model “Point me to the data, I’ll take care of the rest…”  IT maintains the source databases or data warehouses  Use Cognos self-service modeling components to model the database for specific requirements  Users extract subsets of data from source databases via Cognos data sets technology; which are integrated into data modules  Users may upload their own privately maintained curated data from spreadsheets or text files
  • 13. See demos of the three data module architectures To view the video recording and download the slide deck go to https://senturus.com/resources/cognos-data-module- architectures-and-use-cases/. 13
  • 14. 14 Data set libraries • Common data sets for use in user or IT defined data modules • Subject specific dimensional/reference data or summarized fact data • Not meant to store large amounts of data, typically 10-15M rows max • Allows for better performing queries/reports • Stored in common folder structures Databases FM Packages Common Data Sets Stored in Team Content
  • 15. Answers to participant questions 15
  • 16. Cognos Data Module Architectures & Use Cases 16 Q: Is it possible to connect multiple fact tables to the same dimension table or multiple dimension tables in Cognos? For example, if we have five fact tables and three DIM tables with four out of the five fact tables connect to three DIM tables? A: Yes, this typical star schema model is fully supported by data modules. Q: If our users have read only access in Cognos, can they copy data module from their “My Content” and make changes all join? A: Much like a report, users can copy the data module to their My Content and then make changes. But they are no longer linked to the READ ONLY data module and will no longer see any more changes that IT may make.
  • 17. Cognos Data Module Architectures & Use Cases 17 Q: Users in our environment can see Frameworks, but within modules, they can’t see tables in our data warehouse. Are there other configuration/settings that we’re missing? For example, if users go to Microsoft Access, can they see the tables within the warehouse? A: When you create the Cognos data source connection be sure you load the metadata for the schema. This is a button in the data source connection properties. Q: How many Cognos Framework Manager packages can be combined in a data module? A: There is no limit, but it really is a best practice design issue. Make sure your data modules are concise and subject specific.
  • 18. Cognos Data Module Architectures & Use Cases 18 Q: How resource intensive are data modules compared to Framework Manager? Does Cognos suggest additional resources if using DMs vs. FM? A: Since data modules can integrate many different types of data sources – DB Connections, FM packages, data set and uploaded Excel files it will depend on the content of the DMs. A DM with only data sets will generally perform better but you may need to keep an eye on the memory use of the data sets in Cognos. Q: When combining a Cognos Framework Manager package with a data module, does the FM package need to be built in DQM or can it be CQM? A: The FM model needs to be in DQM.
  • 19. Cognos Data Module Architectures & Use Cases 19 Q: If I get an error when I try to bring an ODS package into the Cognos data module will I need help from IT? It says connection information is missing from data source (ODS). I do not have administrative access. A: Like running a report against a package, if the data source connection of the package contains incorrect connection settings, you will need access to that connection. Try calling IT to fix the package connection. Q: If the Cognos Framework Manager package can be either CQM or DQM, are there any advantages or disadvantages between the two? A: DQM is really the better of the two modes. It is the newest mode and uses a 64BIT java engine vs. the 32bit CQM engine. Most current and future Cognos Analytics 11x features will require DQM connections.
  • 20. Cognos Data Module Architectures & Use Cases 20 Q: If I create a hybrid Cognos data module with query subjects that have object-based security, will that security be preserved? A: A data module that brings in Framework Manager package objects will respect the security model of the FM package. Q: In Cognos 11.1.7 can I copy query objects from reports to a data set? A: The 11.1.7 release uses the query tools from the report studio tool set. But we do not believe there is an easy was to import those query objects from reports to the new 11.1.7 data set editor. Q: How can I get the presentation for this webinar? A: Access the deck and the recording at: https://senturus.com/resources/cognos-data-module-architectures-use-cases/
  • 21. Cognos Data Module Architectures & Use Cases 21 Q: With the data set library, how do I save different Cognos data sets for different departments since the data set is saved under the same name? The security is based on department at my organization. A: You can use Team Content folder security to create data sets for departments in different folders. Then the folders are secured for each department. Beyond data sets, you can have one master data set that is in a data module that contains security based on Cognos security groups. Then the data module is the one that is published and then users can link to that data module. Q: Will the architecture model work in Cognos 11.0.13? A: Possibly, but there are so many more data module features added through the 11.1.7 release. We recommend not using that release.
  • 22. Cognos Data Module Architectures & Use Cases 22 Q: Would you recommend using data modules in Cognos 11.0.11? A: We recommend waiting to upgrade to the latest release because of the many improvements to data modules. Q: How much RAM is used when using Cognos data sets? A: Depends on the size of the data set. You can adjust how much memory Cognos devotes to data sets in the advanced settings section of the admin console. Initially it is set to 4GB. Q: How are Cognos data modules validated? A: They are automatically validated in the tool.
  • 23. Cognos Data Module Architectures & Use Cases 23 Q: To improve the performance of data modules, we’ve been creating data sets with data modules and then bring it back to data module. Although this process works, we have been facing issues when trying to combine package. What are the shortcomings when using packages in data modules? A: 11.1.7 has an improved data set editor. The full query painter tools in Report Studio are available in the data set editor. You no longer need to create data modules to create data sets. Using packages in data modules can become confusing since you don’t really see the tables on the relationship diagram editor, and this is by design because of the potential of seeing too many tables. We like to only expose the tables we need from packages in DMs via views. We’ll analyze the requirements and if possible, create a data set from that package that is more subject focused and smaller than the full table in the package.
  • 24. Cognos Data Module Architectures & Use Cases 24 Q: How do Cognos datasets perform against cloud? A: When you join a data set to a cloud table, Cognos will bring the data from the cloud table and join it to the dataset at the Cognos server. Q: Is there possible versioning on Cognos data modeling? A: There is no native versioning so you will need to make copies of a data module. However, Motio has versioning capabilities. Q: In Cognos Framework Manager, can we do complex joins with SQL statements? Can we do those complex joins in Cognos data modules as well? Or are they limited to simple joins? A: The later releases of data modules allow for complex joins. We recommend you start your data module journey with the latest release of Cognos 11.1.7.
  • 25. Cognos Data Module Architectures & Use Cases 25 Q: Can we include several packages in Cognos data modules and then in report editor join queries from various packages in the data modules? A: Technically yes, but it will look messy to report writers. We advise exposing what you need then hide the underlying packages in a data module. Q: How can we make a translation layer in Cognos data modules for reusing translations for role playing dimensions? A: For role playing dimensions, bring in the physical dimension table. Make table view copies of the table then hide the base physical table. Do this in a folder, it acts like a physical namespace layer.
  • 26. Cognos Data Module Architectures & Use Cases 26 Q: When is the auto refresh capability arriving in Cognos? For example, we’d like to use a flat file loaded from a drive. Every time the file is updated, we need to reupload the file. A: Great idea, but we’re not sure when that feature will be arriving. It might be possible to do this via the SDK. Q: Does IBM want users to move off Framework Manager and instead use data modules? A: For new modeling tasks IBM would like you to start with data modules. There are so many Framework Manager models in use that we don’t advise doing a complete 1 for 1 migration of an FM model to a DM. It’s better to just find what parts of that model needs re-engineering and focus on those.
  • 27. Cognos Data Module Architectures & Use Cases 27 Q: Where is the data stored from data sets in Cognos? A: They are stored on the Cognos server in a parquet file format. Q: What are advantages and disadvantages to storing Cognos datasets in a content store database vs. external files? A: Initially they are stored in the content store, but we recommend storing it on the file system because as your user base uses this feature, the content store is going to get too large. With a file system you can devote specific storage locations that could be optimized for retrieval. Q: Does report execution mode changing to 64-bit help in Cognos datasets and data modules or in general? A: Yes.
  • 28. The authority in Business Intelligence 28 Exclusively focused on BI, Senturus is unrivaled in its expertise across the BI stack.
  • 29. Decisions and actions Business needs Bridging the gap 29 Analysis-ready data
  • 30. Full spectrum BI services •Dashboards, reporting and visualizations •Data preparation and modern data warehousing •Hybrid BI environments (migrations, security, etc.) •Software to enable bimodal BI and platform migrations •BI support retainer (expertise on demand) •Training and mentoring 30
  • 31. A long, strong history of success • 20+ years • 1600+ clients • 3000+ projects 31
  • 32. Expand your knowledge 32 Find more resources on the Senturus website: senturus.com/senturus-resources
  • 33. Complete BI training 33 Instructor-led online courses Self-paced learning Mentoring Tailored group sessions
  • 34. Additional resources 34 Insider viewpoints Technical tips Unbiased product reviews Product demos Upcoming events More on this subject
  • 35. © 2020 by Senturus, Inc. This presentation may not be reused or distributed without the written consent of Senturus, Inc. www.senturus.com 888 601 6010 info@senturus.com

Editor's Notes

  1. The first question we usually get is “Can I get a copy of the presentation?” Absolutely! It’s available on Senturus.com. Select the Resources tab and then Resources Library. Or you can click the link that was just posted in the GoToWebinar Control panel. Be sure to bookmark the resource library. It has tons of valuable content addressing a wide variety of business analytics topics.
  2. Joining us today is…..Pedro Ining Pedro joined Senturus in 2010 and brings over 20 years of BI and data warehousing experience to his role. He has been instrumental in implementing data warehousing systems from scratch and has experienced the evolution of the BI industry through several iterations of BI products including Cognos, MicroStrategy and Tableau.
  3. So I think one take away that you should get from this Webinar is that you need to start looking at Data Modules and start exposing your user community To the benefits of Data Modules.
  4. This model could still be an option especially for use cases where the concept of self-service is limited to just running IT developed reports. Usually, the semantic FM Model layer was developed for use by report developers. Semantics layers that are built using this paradigm are typically not well-suited for use by self-service users. The is approach could, however, still enhance a standard FM Package with self-service enhancements like pre-built calculations, better organization, or more specific package subsets of the original FM Model.
  5. This model could still be an option especially for use cases where the concept of self-service is limited to just running IT developed reports. Usually, the semantic FM Model layer was developed for use by report developers. Semantics layers that are built using this paradigm are typically not well-suited for use by self-service users. The is approach could, however, still enhance a standard FM Package with self-service enhancements like pre-built calculations, better organization, or more specific package subsets of the original FM Model.
  6. This model leverages the IT centrally maintained semantic layer but allows users to integrate their own data and enhance the existing IT metadata. In this scenario, only part of the semantic layer is built by IT and the rest could be built by end users. Professional Cognos developers can also build Hybrid models to satisfy specific requirements by end-users such as the loading of their own spreadsheet data. For large legacy Cognos organizations this model is a very appealing choice. Over the years many FM packages have been developed and they typically are very stable and have the data integrity blessing of the central IT organization. Because of the flexibility that Data Modules provide there can be very many permutations of this model. The diagram below shows some common use cases that could be used.
  7. This model could still be an option especially for use cases where the concept of self-service is limited to just running IT developed reports. Usually, the semantic FM Model layer was developed for use by report developers. Semantics layers that are built using this paradigm are typically not well-suited for use by self-service users. The is approach could, however, still enhance a standard FM Package with self-service enhancements like pre-built calculations, better organization, or more specific package subsets of the original FM Model.
  8. This model could still be an option especially for use cases where the concept of self-service is limited to just running IT developed reports. Usually, the semantic FM Model layer was developed for use by report developers. Semantics layers that are built using this paradigm are typically not well-suited for use by self-service users. The is approach could, however, still enhance a standard FM Package with self-service enhancements like pre-built calculations, better organization, or more specific package subsets of the original FM Model.
  9. NOTE we have data modeling classes on all three platforms!
  10. At Senturus we concentrate our expertise on business intelligence with a depth of knowledge across the entire BI stack.
  11. At Senturus, our clients know us for providing clarity from the chaos of complex business requirements, disparate data sources and constantly moving targets. We have made a name for ourselves because of our strength at bridging the gap between IT and business users. We deliver solutions that give you access to reliable, analysis-ready data across the organization so you can quickly and easily get answers at the point of impact: the Decisions you Make and Actions you Take.
  12. Our consultants are leading experts in the field of analytics, with years of pragmatic, real-world expertise and experience advancing the state-of-the-art. We’re so confident in our team and our methodology that we back our projects with a 100% money back guarantee that is unique in the industry.
  13. We have been focused exclusively on business intelligence for 20 years. We work across the spectrum from Fortune 500 to mid market, We solve business problems across many industries and function areas including in the office of finance, sales and marketing, manufacturing, operations, HR and IT Our team is large enough to meet all your business analytics needs yet small enough to provide personal attention.
  14. Senturus has 100s of free resources on our website, from webinars on all things BI, to our fabulous up-to-the-minute, easily consumable blogs.
  15. We provide training in the three top BI platforms. We are ideal for organizations running multiple platforms or those moving from one to another. We can provide training in many modes and can mix and match to suit your user community.
  16. Senturus provides 100s of free resources on our website. We have been committed to sharing our BI expertise for over a decade.